Justin Lutz / Opla_final Public
Set the 'expected outcome' for each sample to the desired outcome to automatically score the impulse.
Sample name Expected outcome Length Anomaly Accuracy Result
on.json.2ticc80r on 10s -0.53 100% 101 on
on.json.2tic99i0 on 10s -0.83 100% 101 on
on.json.2tic7mj1 on 10s -0.79 100% 101 on
on.json.2tic67u9 on 10s -0.78 100% 101 on
on.json.2tic5p81 on 10s -0.64 100% 101 on
on.json.2tic5990 on 10s -0.57 100% 101 on
on.json.2tic4cv4 on 10s -0.34 100% 101 on
on.json.2tic1vm6 on 10s -0.40 100% 101 on
on.json.2tibvr7p on 10s -0.35 100% 101 on
on.json.2tibsjp7 on 10s -0.42 100% 101 on
on.json.2tibrv6q on 10s -0.40 20% 66 off, 20 on, 15 uncertain
off.json.2tibfbin off 10s -0.37 100% 101 off
off.json.2tibeg90 off 10s -0.37 100% 101 off
off.json.2tibe1oa off 10s -0.37 100% 101 off
off.json.2tibas2h off 10s -0.37 100% 101 off
off.json.2tib9vve off 10s -0.37 100% 101 off
off.json.2tib93i0 off 10s -0.37 100% 101 off
off.json.2tib7am8 off 10s -0.37 100% 101 off
off.json.2tib6a5v off 10s -0.31 100% 101 off

Model testing output

Results

Model version:
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